{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9502d5b0",
   "metadata": {},
   "source": [
    "# OpenAI Multi Functions Agent\n",
    "\n",
    "This notebook showcases using an agent that uses the OpenAI functions ability to respond to the prompts of the user using a Large Language Model.\n",
    "\n",
    "Install `openai`, `google-search-results` packages which are required as the LangChain packages call them internally.\n",
    "\n",
    "```bash\n",
    "pip install openai google-search-results\n",
    "```\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c0a83623",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain import SerpAPIWrapper\n",
    "from langchain.agents import initialize_agent, Tool\n",
    "from langchain.agents import AgentType\n",
    "from langchain.chat_models import ChatOpenAI"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86198d9c",
   "metadata": {},
   "source": [
    "The agent is given the ability to perform search functionalities with the respective tool\n",
    "\n",
    "`SerpAPIWrapper`:\n",
    ">This initializes the `SerpAPIWrapper` for search functionality (search).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a2b0a215",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "········\n"
     ]
    }
   ],
   "source": [
    "import getpass\n",
    "import os\n",
    "\n",
    "os.environ[\"SERPAPI_API_KEY\"] = getpass.getpass()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6fefaba2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize the OpenAI language model\n",
    "# Replace <your_api_key> in openai_api_key=\"<your_api_key>\" with your actual OpenAI key.\n",
    "llm = ChatOpenAI(temperature=0, model=\"gpt-3.5-turbo-0613\")\n",
    "\n",
    "# Initialize the SerpAPIWrapper for search functionality\n",
    "# Replace <your_api_key> in serpapi_api_key=\"<your_api_key>\" with your actual SerpAPI key.\n",
    "search = SerpAPIWrapper()\n",
    "\n",
    "# Define a list of tools offered by the agent\n",
    "tools = [\n",
    "    Tool(\n",
    "        name=\"Search\",\n",
    "        func=search.run,\n",
    "        description=\"Useful when you need to answer questions about current events. You should ask targeted questions.\",\n",
    "    ),\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9ff6cee9",
   "metadata": {},
   "outputs": [],
   "source": [
    "mrkl = initialize_agent(\n",
    "    tools, llm, agent=AgentType.OPENAI_MULTI_FUNCTIONS, verbose=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cbe95c81",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Do this so we can see exactly what's going on under the hood\n",
    "import langchain\n",
    "\n",
    "langchain.debug = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ba8e4cbe",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32;1m\u001b[1;3m[chain/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor] Entering Chain run with input:\n",
      "\u001b[0m{\n",
      "  \"input\": \"What is the weather in LA and SF?\"\n",
      "}\n",
      "\u001b[32;1m\u001b[1;3m[llm/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 2:llm:ChatOpenAI] Entering LLM run with input:\n",
      "\u001b[0m{\n",
      "  \"prompts\": [\n",
      "    \"System: You are a helpful AI assistant.\\nHuman: What is the weather in LA and SF?\"\n",
      "  ]\n",
      "}\n",
      "\u001b[36;1m\u001b[1;3m[llm/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 2:llm:ChatOpenAI] [2.91s] Exiting LLM run with output:\n",
      "\u001b[0m{\n",
      "  \"generations\": [\n",
      "    [\n",
      "      {\n",
      "        \"text\": \"\",\n",
      "        \"generation_info\": null,\n",
      "        \"message\": {\n",
      "          \"content\": \"\",\n",
      "          \"additional_kwargs\": {\n",
      "            \"function_call\": {\n",
      "              \"name\": \"tool_selection\",\n",
      "              \"arguments\": \"{\\n  \\\"actions\\\": [\\n    {\\n      \\\"action_name\\\": \\\"Search\\\",\\n      \\\"action\\\": {\\n        \\\"tool_input\\\": \\\"weather in Los Angeles\\\"\\n      }\\n    },\\n    {\\n      \\\"action_name\\\": \\\"Search\\\",\\n      \\\"action\\\": {\\n        \\\"tool_input\\\": \\\"weather in San Francisco\\\"\\n      }\\n    }\\n  ]\\n}\"\n",
      "            }\n",
      "          },\n",
      "          \"example\": false\n",
      "        }\n",
      "      }\n",
      "    ]\n",
      "  ],\n",
      "  \"llm_output\": {\n",
      "    \"token_usage\": {\n",
      "      \"prompt_tokens\": 81,\n",
      "      \"completion_tokens\": 75,\n",
      "      \"total_tokens\": 156\n",
      "    },\n",
      "    \"model_name\": \"gpt-3.5-turbo-0613\"\n",
      "  },\n",
      "  \"run\": null\n",
      "}\n",
      "\u001b[32;1m\u001b[1;3m[tool/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 3:tool:Search] Entering Tool run with input:\n",
      "\u001b[0m\"{'tool_input': 'weather in Los Angeles'}\"\n",
      "\u001b[36;1m\u001b[1;3m[tool/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 3:tool:Search] [608.693ms] Exiting Tool run with output:\n",
      "\u001b[0m\"Mostly cloudy early, then sunshine for the afternoon. High 76F. Winds SW at 5 to 10 mph. Humidity59%.\"\n",
      "\u001b[32;1m\u001b[1;3m[tool/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 4:tool:Search] Entering Tool run with input:\n",
      "\u001b[0m\"{'tool_input': 'weather in San Francisco'}\"\n",
      "\u001b[36;1m\u001b[1;3m[tool/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 4:tool:Search] [517.475ms] Exiting Tool run with output:\n",
      "\u001b[0m\"Partly cloudy this evening, then becoming cloudy after midnight. Low 53F. Winds WSW at 10 to 20 mph. Humidity83%.\"\n",
      "\u001b[32;1m\u001b[1;3m[llm/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 5:llm:ChatOpenAI] Entering LLM run with input:\n",
      "\u001b[0m{\n",
      "  \"prompts\": [\n",
      "    \"System: You are a helpful AI assistant.\\nHuman: What is the weather in LA and SF?\\nAI: {'name': 'tool_selection', 'arguments': '{\\\\n  \\\"actions\\\": [\\\\n    {\\\\n      \\\"action_name\\\": \\\"Search\\\",\\\\n      \\\"action\\\": {\\\\n        \\\"tool_input\\\": \\\"weather in Los Angeles\\\"\\\\n      }\\\\n    },\\\\n    {\\\\n      \\\"action_name\\\": \\\"Search\\\",\\\\n      \\\"action\\\": {\\\\n        \\\"tool_input\\\": \\\"weather in San Francisco\\\"\\\\n      }\\\\n    }\\\\n  ]\\\\n}'}\\nFunction: Mostly cloudy early, then sunshine for the afternoon. High 76F. Winds SW at 5 to 10 mph. Humidity59%.\\nAI: {'name': 'tool_selection', 'arguments': '{\\\\n  \\\"actions\\\": [\\\\n    {\\\\n      \\\"action_name\\\": \\\"Search\\\",\\\\n      \\\"action\\\": {\\\\n        \\\"tool_input\\\": \\\"weather in Los Angeles\\\"\\\\n      }\\\\n    },\\\\n    {\\\\n      \\\"action_name\\\": \\\"Search\\\",\\\\n      \\\"action\\\": {\\\\n        \\\"tool_input\\\": \\\"weather in San Francisco\\\"\\\\n      }\\\\n    }\\\\n  ]\\\\n}'}\\nFunction: Partly cloudy this evening, then becoming cloudy after midnight. Low 53F. Winds WSW at 10 to 20 mph. Humidity83%.\"\n",
      "  ]\n",
      "}\n",
      "\u001b[36;1m\u001b[1;3m[llm/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 5:llm:ChatOpenAI] [2.33s] Exiting LLM run with output:\n",
      "\u001b[0m{\n",
      "  \"generations\": [\n",
      "    [\n",
      "      {\n",
      "        \"text\": \"The weather in Los Angeles is mostly cloudy with a high of 76°F and a humidity of 59%. The weather in San Francisco is partly cloudy in the evening, becoming cloudy after midnight, with a low of 53°F and a humidity of 83%.\",\n",
      "        \"generation_info\": null,\n",
      "        \"message\": {\n",
      "          \"content\": \"The weather in Los Angeles is mostly cloudy with a high of 76°F and a humidity of 59%. The weather in San Francisco is partly cloudy in the evening, becoming cloudy after midnight, with a low of 53°F and a humidity of 83%.\",\n",
      "          \"additional_kwargs\": {},\n",
      "          \"example\": false\n",
      "        }\n",
      "      }\n",
      "    ]\n",
      "  ],\n",
      "  \"llm_output\": {\n",
      "    \"token_usage\": {\n",
      "      \"prompt_tokens\": 307,\n",
      "      \"completion_tokens\": 54,\n",
      "      \"total_tokens\": 361\n",
      "    },\n",
      "    \"model_name\": \"gpt-3.5-turbo-0613\"\n",
      "  },\n",
      "  \"run\": null\n",
      "}\n",
      "\u001b[36;1m\u001b[1;3m[chain/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor] [6.37s] Exiting Chain run with output:\n",
      "\u001b[0m{\n",
      "  \"output\": \"The weather in Los Angeles is mostly cloudy with a high of 76°F and a humidity of 59%. The weather in San Francisco is partly cloudy in the evening, becoming cloudy after midnight, with a low of 53°F and a humidity of 83%.\"\n",
      "}\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'The weather in Los Angeles is mostly cloudy with a high of 76°F and a humidity of 59%. The weather in San Francisco is partly cloudy in the evening, becoming cloudy after midnight, with a low of 53°F and a humidity of 83%.'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mrkl.run(\"What is the weather in LA and SF?\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d31d4c09",
   "metadata": {},
   "source": [
    "## Configuring max iteration behavior\n",
    "\n",
    "To make sure that our agent doesn't get stuck in excessively long loops, we can set `max_iterations`. We can also set an early stopping method, which will determine our agent's behavior once the number of max iterations is hit. By default, the early stopping uses method `force` which just returns that constant string. Alternatively, you could specify method `generate` which then does one FINAL pass through the LLM to generate an output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9f5f6743",
   "metadata": {},
   "outputs": [],
   "source": [
    "mrkl = initialize_agent(\n",
    "    tools,\n",
    "    llm,\n",
    "    agent=AgentType.OPENAI_FUNCTIONS,\n",
    "    verbose=True,\n",
    "    max_iterations=2,\n",
    "    early_stopping_method=\"generate\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4362ebc7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32;1m\u001b[1;3m[chain/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor] Entering Chain run with input:\n",
      "\u001b[0m{\n",
      "  \"input\": \"What is the weather in NYC today, yesterday, and the day before?\"\n",
      "}\n",
      "\u001b[32;1m\u001b[1;3m[llm/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 2:llm:ChatOpenAI] Entering LLM run with input:\n",
      "\u001b[0m{\n",
      "  \"prompts\": [\n",
      "    \"System: You are a helpful AI assistant.\\nHuman: What is the weather in NYC today, yesterday, and the day before?\"\n",
      "  ]\n",
      "}\n",
      "\u001b[36;1m\u001b[1;3m[llm/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 2:llm:ChatOpenAI] [1.27s] Exiting LLM run with output:\n",
      "\u001b[0m{\n",
      "  \"generations\": [\n",
      "    [\n",
      "      {\n",
      "        \"text\": \"\",\n",
      "        \"generation_info\": null,\n",
      "        \"message\": {\n",
      "          \"lc\": 1,\n",
      "          \"type\": \"constructor\",\n",
      "          \"id\": [\n",
      "            \"langchain\",\n",
      "            \"schema\",\n",
      "            \"messages\",\n",
      "            \"AIMessage\"\n",
      "          ],\n",
      "          \"kwargs\": {\n",
      "            \"content\": \"\",\n",
      "            \"additional_kwargs\": {\n",
      "              \"function_call\": {\n",
      "                \"name\": \"Search\",\n",
      "                \"arguments\": \"{\\n  \\\"query\\\": \\\"weather in NYC today\\\"\\n}\"\n",
      "              }\n",
      "            }\n",
      "          }\n",
      "        }\n",
      "      }\n",
      "    ]\n",
      "  ],\n",
      "  \"llm_output\": {\n",
      "    \"token_usage\": {\n",
      "      \"prompt_tokens\": 79,\n",
      "      \"completion_tokens\": 17,\n",
      "      \"total_tokens\": 96\n",
      "    },\n",
      "    \"model_name\": \"gpt-3.5-turbo-0613\"\n",
      "  },\n",
      "  \"run\": null\n",
      "}\n",
      "\u001b[32;1m\u001b[1;3m[tool/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 3:tool:Search] Entering Tool run with input:\n",
      "\u001b[0m\"{'query': 'weather in NYC today'}\"\n",
      "\u001b[36;1m\u001b[1;3m[tool/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 3:tool:Search] [3.84s] Exiting Tool run with output:\n",
      "\u001b[0m\"10:00 am · Feels Like85° · WindSE 4 mph · Humidity78% · UV Index3 of 11 · Cloud Cover81% · Rain Amount0 in ...\"\n",
      "\u001b[32;1m\u001b[1;3m[llm/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 4:llm:ChatOpenAI] Entering LLM run with input:\n",
      "\u001b[0m{\n",
      "  \"prompts\": [\n",
      "    \"System: You are a helpful AI assistant.\\nHuman: What is the weather in NYC today, yesterday, and the day before?\\nAI: {'name': 'Search', 'arguments': '{\\\\n  \\\"query\\\": \\\"weather in NYC today\\\"\\\\n}'}\\nFunction: 10:00 am · Feels Like85° · WindSE 4 mph · Humidity78% · UV Index3 of 11 · Cloud Cover81% · Rain Amount0 in ...\"\n",
      "  ]\n",
      "}\n",
      "\u001b[36;1m\u001b[1;3m[llm/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 4:llm:ChatOpenAI] [1.24s] Exiting LLM run with output:\n",
      "\u001b[0m{\n",
      "  \"generations\": [\n",
      "    [\n",
      "      {\n",
      "        \"text\": \"\",\n",
      "        \"generation_info\": null,\n",
      "        \"message\": {\n",
      "          \"lc\": 1,\n",
      "          \"type\": \"constructor\",\n",
      "          \"id\": [\n",
      "            \"langchain\",\n",
      "            \"schema\",\n",
      "            \"messages\",\n",
      "            \"AIMessage\"\n",
      "          ],\n",
      "          \"kwargs\": {\n",
      "            \"content\": \"\",\n",
      "            \"additional_kwargs\": {\n",
      "              \"function_call\": {\n",
      "                \"name\": \"Search\",\n",
      "                \"arguments\": \"{\\n  \\\"query\\\": \\\"weather in NYC yesterday\\\"\\n}\"\n",
      "              }\n",
      "            }\n",
      "          }\n",
      "        }\n",
      "      }\n",
      "    ]\n",
      "  ],\n",
      "  \"llm_output\": {\n",
      "    \"token_usage\": {\n",
      "      \"prompt_tokens\": 142,\n",
      "      \"completion_tokens\": 17,\n",
      "      \"total_tokens\": 159\n",
      "    },\n",
      "    \"model_name\": \"gpt-3.5-turbo-0613\"\n",
      "  },\n",
      "  \"run\": null\n",
      "}\n",
      "\u001b[32;1m\u001b[1;3m[tool/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 5:tool:Search] Entering Tool run with input:\n",
      "\u001b[0m\"{'query': 'weather in NYC yesterday'}\"\n",
      "\u001b[36;1m\u001b[1;3m[tool/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 5:tool:Search] [1.15s] Exiting Tool run with output:\n",
      "\u001b[0m\"New York Temperature Yesterday. Maximum temperature yesterday: 81 °F (at 1:51 pm) Minimum temperature yesterday: 72 °F (at 7:17 pm) Average temperature ...\"\n",
      "\u001b[32;1m\u001b[1;3m[llm/start]\u001b[0m \u001b[1m[1:llm:ChatOpenAI] Entering LLM run with input:\n",
      "\u001b[0m{\n",
      "  \"prompts\": [\n",
      "    \"System: You are a helpful AI assistant.\\nHuman: What is the weather in NYC today, yesterday, and the day before?\\nAI: {'name': 'Search', 'arguments': '{\\\\n  \\\"query\\\": \\\"weather in NYC today\\\"\\\\n}'}\\nFunction: 10:00 am · Feels Like85° · WindSE 4 mph · Humidity78% · UV Index3 of 11 · Cloud Cover81% · Rain Amount0 in ...\\nAI: {'name': 'Search', 'arguments': '{\\\\n  \\\"query\\\": \\\"weather in NYC yesterday\\\"\\\\n}'}\\nFunction: New York Temperature Yesterday. Maximum temperature yesterday: 81 °F (at 1:51 pm) Minimum temperature yesterday: 72 °F (at 7:17 pm) Average temperature ...\"\n",
      "  ]\n",
      "}\n",
      "\u001b[36;1m\u001b[1;3m[llm/end]\u001b[0m \u001b[1m[1:llm:ChatOpenAI] [2.68s] Exiting LLM run with output:\n",
      "\u001b[0m{\n",
      "  \"generations\": [\n",
      "    [\n",
      "      {\n",
      "        \"text\": \"Today in NYC, the weather is currently 85°F with a southeast wind of 4 mph. The humidity is at 78% and there is 81% cloud cover. There is no rain expected today.\\n\\nYesterday in NYC, the maximum temperature was 81°F at 1:51 pm, and the minimum temperature was 72°F at 7:17 pm.\\n\\nFor the day before yesterday, I do not have the specific weather information.\",\n",
      "        \"generation_info\": null,\n",
      "        \"message\": {\n",
      "          \"lc\": 1,\n",
      "          \"type\": \"constructor\",\n",
      "          \"id\": [\n",
      "            \"langchain\",\n",
      "            \"schema\",\n",
      "            \"messages\",\n",
      "            \"AIMessage\"\n",
      "          ],\n",
      "          \"kwargs\": {\n",
      "            \"content\": \"Today in NYC, the weather is currently 85°F with a southeast wind of 4 mph. The humidity is at 78% and there is 81% cloud cover. There is no rain expected today.\\n\\nYesterday in NYC, the maximum temperature was 81°F at 1:51 pm, and the minimum temperature was 72°F at 7:17 pm.\\n\\nFor the day before yesterday, I do not have the specific weather information.\",\n",
      "            \"additional_kwargs\": {}\n",
      "          }\n",
      "        }\n",
      "      }\n",
      "    ]\n",
      "  ],\n",
      "  \"llm_output\": {\n",
      "    \"token_usage\": {\n",
      "      \"prompt_tokens\": 160,\n",
      "      \"completion_tokens\": 91,\n",
      "      \"total_tokens\": 251\n",
      "    },\n",
      "    \"model_name\": \"gpt-3.5-turbo-0613\"\n",
      "  },\n",
      "  \"run\": null\n",
      "}\n",
      "\u001b[36;1m\u001b[1;3m[chain/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor] [10.18s] Exiting Chain run with output:\n",
      "\u001b[0m{\n",
      "  \"output\": \"Today in NYC, the weather is currently 85°F with a southeast wind of 4 mph. The humidity is at 78% and there is 81% cloud cover. There is no rain expected today.\\n\\nYesterday in NYC, the maximum temperature was 81°F at 1:51 pm, and the minimum temperature was 72°F at 7:17 pm.\\n\\nFor the day before yesterday, I do not have the specific weather information.\"\n",
      "}\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'Today in NYC, the weather is currently 85°F with a southeast wind of 4 mph. The humidity is at 78% and there is 81% cloud cover. There is no rain expected today.\\n\\nYesterday in NYC, the maximum temperature was 81°F at 1:51 pm, and the minimum temperature was 72°F at 7:17 pm.\\n\\nFor the day before yesterday, I do not have the specific weather information.'"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mrkl.run(\"What is the weather in NYC today, yesterday, and the day before?\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "067a8d3e",
   "metadata": {},
   "source": [
    "Notice that we never get around to looking up the weather the day before yesterday, due to hitting our `max_iterations` limit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c3318a11",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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